Pandas Profiling Report

Dataset statistics

Number of variables	15
Number of observations	6745
Missing cells	22821
Missing cells (%)	22.6%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	790.6 KiB
Average record size in memory	120.0 B

Variable types

Categorical	6
Numeric	9

Warnings

`country` has a high cardinality: 137 distinct values	High cardinality
`iso_code` has a high cardinality: 137 distinct values	High cardinality
`date` has a high cardinality: 94 distinct values	High cardinality
`source_name` has a high cardinality: 81 distinct values	High cardinality
`source_website` has a high cardinality: 133 distinct values	High cardinality
`total_vaccinations` is highly correlated with `people_vaccinated` and 2 other fields	High correlation
`people_vaccinated` is highly correlated with `total_vaccinations` and 1 other fields	High correlation
`people_fully_vaccinated` is highly correlated with `total_vaccinations`	High correlation
`daily_vaccinations_raw` is highly correlated with `daily_vaccinations`	High correlation
`daily_vaccinations` is highly correlated with `total_vaccinations` and 2 other fields	High correlation
`total_vaccinations_per_hundred` is highly correlated with `people_vaccinated_per_hundred` and 1 other fields	High correlation
`people_vaccinated_per_hundred` is highly correlated with `total_vaccinations_per_hundred`	High correlation
`people_fully_vaccinated_per_hundred` is highly correlated with `total_vaccinations_per_hundred`	High correlation
`total_vaccinations` has 2502 (37.1%) missing values	Missing
`people_vaccinated` has 2960 (43.9%) missing values	Missing
`people_fully_vaccinated` has 4169 (61.8%) missing values	Missing
`daily_vaccinations_raw` has 3169 (47.0%) missing values	Missing
`daily_vaccinations` has 195 (2.9%) missing values	Missing
`total_vaccinations_per_hundred` has 2502 (37.1%) missing values	Missing
`people_vaccinated_per_hundred` has 2960 (43.9%) missing values	Missing
`people_fully_vaccinated_per_hundred` has 4169 (61.8%) missing values	Missing
`daily_vaccinations_per_million` has 195 (2.9%) missing values	Missing
`total_vaccinations` has 75 (1.1%) zeros	Zeros
`daily_vaccinations_raw` has 72 (1.1%) zeros	Zeros
`total_vaccinations_per_hundred` has 131 (1.9%) zeros	Zeros
`people_vaccinated_per_hundred` has 104 (1.5%) zeros	Zeros

Reproduction

Analysis started	2021-03-19 07:01:21.332254
Analysis finished	2021-03-19 07:01:39.458398
Duration	18.13 seconds
Software version	pandas-profiling v2.11.0
Download configuration	config.yaml

country
Categorical

HIGH CARDINALITY

Distinct	137
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	52.8 KiB

Wales	93
England	93
Northern Ireland	93
Scotland	93
Canada	93
Other values (132)	6280

Length

Max length	24
Median length	7
Mean length	8.057968866
Min length	4

Characters and Unicode

Total characters	54351
Distinct characters	51
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	Albania
2nd row	Albania
3rd row	Albania
4th row	Albania
5th row	Albania

Value	Count	Frequency (%)
Wales	93	1.4%
England	93	1.4%
Northern Ireland	93	1.4%
Scotland	93	1.4%
Canada	93	1.4%
United Kingdom	93	1.4%
China	90	1.3%
Russia	90	1.3%
Israel	88	1.3%
United States	87	1.3%
Other values (127)	5832	86.5%

Histogram of lengths of the category

Value	Count	Frequency (%)
united	251	3.1%
islands	174	2.2%
ireland	166	2.1%
northern	102	1.3%
kingdom	93	1.2%
scotland	93	1.2%
england	93	1.2%
wales	93	1.2%
canada	93	1.2%
china	90	1.1%
Other values (146)	6743	84.4%

Most occurring characters

Value	Count	Frequency (%)
a	8184	15.1%
n	4644	8.5%
e	4090	7.5%
i	3828	7.0%
r	3506	6.5%
l	2724	5.0%
o	2501	4.6%
d	2274	4.2%
t	2224	4.1%
s	1994	3.7%
Other values (41)	18382	33.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	45219	83.2%
Uppercase Letter	7870	14.5%
Space Separator	1246	2.3%
Other Punctuation	16	< 0.1%

Most frequent character per category

Value	Count	Frequency (%)
a	8184	18.1%
n	4644	10.3%
e	4090	9.0%
i	3828	8.5%
r	3506	7.8%
l	2724	6.0%
o	2501	5.5%
d	2274	5.0%
t	2224	4.9%
s	1994	4.4%
Other values (15)	9250	20.5%

Value	Count	Frequency (%)
S	981	12.5%
I	790	10.0%
C	766	9.7%
A	613	7.8%
B	586	7.4%
M	546	6.9%
L	374	4.8%
G	364	4.6%
E	328	4.2%
R	309	3.9%
Other values (14)	2213	28.1%

Value	Count	Frequency (%)
	1246	100.0%

Value	Count	Frequency (%)
'	16	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	53089	97.7%
Common	1262	2.3%

Most frequent character per script

Value	Count	Frequency (%)
a	8184	15.4%
n	4644	8.7%
e	4090	7.7%
i	3828	7.2%
r	3506	6.6%
l	2724	5.1%
o	2501	4.7%
d	2274	4.3%
t	2224	4.2%
s	1994	3.8%
Other values (39)	17120	32.2%

Value	Count	Frequency (%)
	1246	98.7%
'	16	1.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	54351	100.0%

Most frequent character per block

Value	Count	Frequency (%)
a	8184	15.1%
n	4644	8.5%
e	4090	7.5%
i	3828	7.0%
r	3506	6.5%
l	2724	5.0%
o	2501	4.6%
d	2274	4.2%
t	2224	4.1%
s	1994	3.7%
Other values (41)	18382	33.8%

iso_code
Categorical

HIGH CARDINALITY

Distinct	137
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	52.8 KiB

GBR	93
OWID_NIR	93
OWID_SCT	93
OWID_WLS	93
CAN	93
Other values (132)	6280

Length

Max length	8
Median length	3
Mean length	3.282431431
Min length	3

Characters and Unicode

Total characters	22140
Distinct characters	27
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	ALB
2nd row	ALB
3rd row	ALB
4th row	ALB
5th row	ALB

Value	Count	Frequency (%)
GBR	93	1.4%
OWID_NIR	93	1.4%
OWID_SCT	93	1.4%
OWID_WLS	93	1.4%
CAN	93	1.4%
OWID_ENG	93	1.4%
CHN	90	1.3%
RUS	90	1.3%
ISR	88	1.3%
USA	87	1.3%
Other values (127)	5832	86.5%

Histogram of lengths of the category

Value	Count	Frequency (%)
owid_nir	93	1.4%
owid_sct	93	1.4%
owid_wls	93	1.4%
can	93	1.4%
owid_eng	93	1.4%
gbr	93	1.4%
rus	90	1.3%
chn	90	1.3%
isr	88	1.3%
usa	87	1.3%
Other values (127)	5832	86.5%

Most occurring characters

Value	Count	Frequency (%)
R	1988	9.0%
A	1604	7.2%
N	1432	6.5%
S	1343	6.1%
L	1315	5.9%
I	1299	5.9%
C	1118	5.0%
E	1104	5.0%
U	1015	4.6%
O	1006	4.5%
Other values (17)	8916	40.3%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	21759	98.3%
Connector Punctuation	381	1.7%

Most frequent character per category

Value	Count	Frequency (%)
R	1988	9.1%
A	1604	7.4%
N	1432	6.6%
S	1343	6.2%
L	1315	6.0%
I	1299	6.0%
C	1118	5.1%
E	1104	5.1%
U	1015	4.7%
O	1006	4.6%
Other values (16)	8535	39.2%

Value	Count	Frequency (%)
_	381	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	21759	98.3%
Common	381	1.7%

Most frequent character per script

Value	Count	Frequency (%)
R	1988	9.1%
A	1604	7.4%
N	1432	6.6%
S	1343	6.2%
L	1315	6.0%
I	1299	6.0%
C	1118	5.1%
E	1104	5.1%
U	1015	4.7%
O	1006	4.6%
Other values (16)	8535	39.2%

Value	Count	Frequency (%)
_	381	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	22140	100.0%

Most frequent character per block

Value	Count	Frequency (%)
R	1988	9.0%
A	1604	7.2%
N	1432	6.5%
S	1343	6.1%
L	1315	5.9%
I	1299	5.9%
C	1118	5.0%
E	1104	5.0%
U	1015	4.6%
O	1006	4.5%
Other values (17)	8916	40.3%

date
Categorical

HIGH CARDINALITY

Distinct	94
Distinct (%)	1.4%
Missing	0
Missing (%)	0.0%
Memory size	52.8 KiB

2021-03-07	116
2021-03-01	116
2021-03-08	116
2021-03-10	115
2021-03-04	115
Other values (89)	6167

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	67450
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2021-01-10
2nd row	2021-01-11
3rd row	2021-01-12
4th row	2021-01-13
5th row	2021-01-14

Value	Count	Frequency (%)
2021-03-07	116	1.7%
2021-03-01	116	1.7%
2021-03-08	116	1.7%
2021-03-10	115	1.7%
2021-03-04	115	1.7%
2021-03-05	115	1.7%
2021-03-06	115	1.7%
2021-03-09	115	1.7%
2021-02-28	114	1.7%
2021-03-03	114	1.7%
Other values (84)	5594	82.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
2021-03-07	116	1.7%
2021-03-01	116	1.7%
2021-03-08	116	1.7%
2021-03-10	115	1.7%
2021-03-04	115	1.7%
2021-03-05	115	1.7%
2021-03-06	115	1.7%
2021-03-09	115	1.7%
2021-02-28	114	1.7%
2021-03-03	114	1.7%
Other values (84)	5594	82.9%

Most occurring characters

Value	Count	Frequency (%)
2	19174	28.4%
0	16307	24.2%
-	13490	20.0%
1	11851	17.6%
3	2660	3.9%
5	707	1.0%
4	704	1.0%
6	674	1.0%
8	670	1.0%
7	651	1.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	53960	80.0%
Dash Punctuation	13490	20.0%

Most frequent character per category

Value	Count	Frequency (%)
2	19174	35.5%
0	16307	30.2%
1	11851	22.0%
3	2660	4.9%
5	707	1.3%
4	704	1.3%
6	674	1.2%
8	670	1.2%
7	651	1.2%
9	562	1.0%

Value	Count	Frequency (%)
-	13490	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	67450	100.0%

Most frequent character per script

Value	Count	Frequency (%)
2	19174	28.4%
0	16307	24.2%
-	13490	20.0%
1	11851	17.6%
3	2660	3.9%
5	707	1.0%
4	704	1.0%
6	674	1.0%
8	670	1.0%
7	651	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	67450	100.0%

Most frequent character per block

Value	Count	Frequency (%)
2	19174	28.4%
0	16307	24.2%
-	13490	20.0%
1	11851	17.6%
3	2660	3.9%
5	707	1.0%
4	704	1.0%
6	674	1.0%
8	670	1.0%
7	651	1.0%

total_vaccinations
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING
ZEROS

Distinct	4064
Distinct (%)	95.8%
Missing	2502
Missing (%)	37.1%
Infinite	0
Infinite (%)	0.0%

Mean	2285175.267
Minimum	0
Maximum	110737856
Zeros	75
Zeros (%)	1.1%
Memory size	52.8 KiB

Quantile statistics

Minimum	0
5-th percentile	1882.7
Q1	36650
median	250000
Q3	1175071
95-th percentile	9187623.7
Maximum	110737856
Range	110737856
Interquartile range (IQR)	1138421

Descriptive statistics

Standard deviation	8041932.547
Coefficient of variation (CV)	3.519175383
Kurtosis	80.6065853
Mean	2285175.267
Median Absolute Deviation (MAD)	242087
Skewness	8.129045652
Sum	9695998658
Variance	6.467267908 × 10¹³
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	75	1.1%
12441	13	0.2%
8649	8	0.1%
10702	7	0.1%
67424	4	0.1%
72426	3	< 0.1%
40000	3	< 0.1%
13329	3	< 0.1%
8772	3	< 0.1%
4000	3	< 0.1%
Other values (4054)	4121	61.1%
(Missing)	2502	37.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	75	1.1%
5	2	< 0.1%
12	1	< 0.1%
13	1	< 0.1%
18	1	< 0.1%

Value	Count	Frequency (%)
110737856	1	< 0.1%
109081860	1	< 0.1%
107060274	1	< 0.1%
105703501	1	< 0.1%
101128005	1	< 0.1%

people_vaccinated
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING

Distinct	3625
Distinct (%)	95.8%
Missing	2960
Missing (%)	43.9%
Infinite	0
Infinite (%)	0.0%

Mean	1858055.057
Minimum	0
Maximum	72135616
Zeros	60
Zeros (%)	0.9%
Memory size	52.8 KiB

Quantile statistics

Minimum	0
5-th percentile	2193.6
Q1	34772
median	230329
Q3	942017
95-th percentile	7892472.8
Maximum	72135616
Range	72135616
Interquartile range (IQR)	907245

Descriptive statistics

Standard deviation	5975595.993
Coefficient of variation (CV)	3.216048939
Kurtosis	54.62166687
Mean	1858055.057
Median Absolute Deviation (MAD)	217862
Skewness	6.663408402
Sum	7032738389
Variance	3.570774747 × 10¹³
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	60	0.9%
24773	10	0.1%
8649	8	0.1%
10702	8	0.1%
57024	6	0.1%
10325	4	0.1%
250000	3	< 0.1%
640115	3	< 0.1%
30000	3	< 0.1%
2000	3	< 0.1%
Other values (3615)	3677	54.5%
(Missing)	2960	43.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	60	0.9%
5	1	< 0.1%
13	1	< 0.1%
18	1	< 0.1%
20	1	< 0.1%

Value	Count	Frequency (%)
72135616	1	< 0.1%
71054445	1	< 0.1%
69784210	1	< 0.1%
68884011	1	< 0.1%
65965305	1	< 0.1%

people_fully_vaccinated
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING

Distinct	2458
Distinct (%)	95.4%
Missing	4169
Missing (%)	61.8%
Infinite	0
Infinite (%)	0.0%

Mean	749927.3195
Minimum	1
Maximum	39042345
Zeros	0
Zeros (%)	0.0%
Memory size	52.8 KiB

Quantile statistics

Minimum	1
5-th percentile	2039
Q1	17388
median	92566
Q3	448936.25
95-th percentile	2454456.25
Maximum	39042345
Range	39042344
Interquartile range (IQR)	431548.25

Descriptive statistics

Standard deviation	3021858.416
Coefficient of variation (CV)	4.029535046
Kurtosis	86.05404952
Mean	749927.3195
Median Absolute Deviation (MAD)	88135
Skewness	8.775792438
Sum	1931812775
Variance	9.131628285 × 10¹²
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
19019	11	0.2%
12272	9	0.1%
6228	7	0.1%
55767	6	0.1%
8366	6	0.1%
10400	4	0.1%
2	4	0.1%
1928	4	0.1%
5	4	0.1%
9785	3	< 0.1%
Other values (2448)	2518	37.3%
(Missing)	4169	61.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	2	< 0.1%
2	4	0.1%
5	4	0.1%
8	1	< 0.1%
12	1	< 0.1%

Value	Count	Frequency (%)
39042345	1	< 0.1%
38335432	1	< 0.1%
37459269	1	< 0.1%
36929777	1	< 0.1%
35000159	1	< 0.1%

daily_vaccinations_raw
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING
ZEROS

Distinct	3319
Distinct (%)	92.8%
Missing	3169
Missing (%)	47.0%
Infinite	0
Infinite (%)	0.0%

Mean	85386.07802
Minimum	0
Maximum	4575496
Zeros	72
Zeros (%)	1.1%
Memory size	52.8 KiB

Quantile statistics

Minimum	0
5-th percentile	144.75
Q1	2625.75
median	13446.5
Q3	57524.25
95-th percentile	352953.5
Maximum	4575496
Range	4575496
Interquartile range (IQR)	54898.5

Descriptive statistics

Standard deviation	259638.0348
Coefficient of variation (CV)	3.040753725
Kurtosis	67.18693
Mean	85386.07802
Median Absolute Deviation (MAD)	12598.5
Skewness	7.162530149
Sum	305340615
Variance	6.741190911 × 10¹⁰
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	72	1.1%
1	9	0.1%
534	5	0.1%
30	4	0.1%
8	4	0.1%
930	4	0.1%
3000	4	0.1%
654	4	0.1%
1074	3	< 0.1%
90	3	< 0.1%
Other values (3309)	3464	51.4%
(Missing)	3169	47.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	72	1.1%
1	9	0.1%
2	1	< 0.1%
3	2	< 0.1%
4	1	< 0.1%

Value	Count	Frequency (%)
4575496	1	< 0.1%
3039394	1	< 0.1%
2924112	1	< 0.1%
2904229	1	< 0.1%
2482603	1	< 0.1%

daily_vaccinations
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING

Distinct	4736
Distinct (%)	72.3%
Missing	195
Missing (%)	2.9%
Infinite	0
Infinite (%)	0.0%

Mean	59235.52702
Minimum	1
Maximum	2541597
Zeros	0
Zeros (%)	0.0%
Memory size	52.8 KiB

Quantile statistics

Minimum	1
5-th percentile	112.45
Q1	1089
median	6424
Q3	28231.25
95-th percentile	270363.8
Maximum	2541597
Range	2541596
Interquartile range (IQR)	27142.25

Descriptive statistics

Standard deviation	196717.9036
Coefficient of variation (CV)	3.320944599
Kurtosis	57.2600865
Mean	59235.52702
Median Absolute Deviation (MAD)	6112.5
Skewness	6.898057901
Sum	387992702
Variance	3.869793358 × 10¹⁰
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
403	52	0.8%
7712	47	0.7%
275	41	0.6%
294	40	0.6%
1351	37	0.5%
77	35	0.5%
895	32	0.5%
222	31	0.5%
1121	30	0.4%
63	30	0.4%
Other values (4726)	6175	91.5%
(Missing)	195	2.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
4	1	< 0.1%
9	1	< 0.1%

Value	Count	Frequency (%)
2541597	1	< 0.1%
2435037	1	< 0.1%
2427430	1	< 0.1%
2386932	1	< 0.1%
2302844	1	< 0.1%

total_vaccinations_per_hundred
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING
ZEROS

Distinct	1713
Distinct (%)	40.4%
Missing	2502
Missing (%)	37.1%
Infinite	0
Infinite (%)	0.0%

Mean	9.118823945
Minimum	0
Maximum	143.35
Zeros	131
Zeros (%)	1.9%
Memory size	52.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0.02
Q1	0.72
median	3.43
Q3	9.56
95-th percentile	36.529
Maximum	143.35
Range	143.35
Interquartile range (IQR)	8.84

Descriptive statistics

Standard deviation	16.49915304
Coefficient of variation (CV)	1.809350979
Kurtosis	18.69235955
Mean	9.118823945
Median Absolute Deviation (MAD)	3.15
Skewness	3.857395855
Sum	38691.17
Variance	272.2220509
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	131	1.9%
0.01	59	0.9%
0.02	43	0.6%
0.05	34	0.5%
0.03	33	0.5%
0.04	30	0.4%
0.06	25	0.4%
0.29	25	0.4%
0.07	24	0.4%
0.24	22	0.3%
Other values (1703)	3817	56.6%
(Missing)	2502	37.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	131	1.9%
0.01	59	0.9%
0.02	43	0.6%
0.03	33	0.5%
0.04	30	0.4%

Value	Count	Frequency (%)
143.35	1	< 0.1%
140.13	1	< 0.1%
136.94	2	< 0.1%
135.02	1	< 0.1%
133.25	2	< 0.1%

people_vaccinated_per_hundred
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING
ZEROS

Distinct	1446
Distinct (%)	38.2%
Missing	2960
Missing (%)	43.9%
Infinite	0
Infinite (%)	0.0%

Mean	7.02803963
Minimum	0
Maximum	88.06
Zeros	104
Zeros (%)	1.5%
Memory size	52.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0.02
Q1	0.72
median	2.99
Q3	7.49
95-th percentile	31.262
Maximum	88.06
Range	88.06
Interquartile range (IQR)	6.77

Descriptive statistics

Standard deviation	11.31155976
Coefficient of variation (CV)	1.609490037
Kurtosis	12.55254537
Mean	7.02803963
Median Absolute Deviation (MAD)	2.63
Skewness	3.157005363
Sum	26601.13
Variance	127.9513843
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	104	1.5%
0.01	55	0.8%
0.02	40	0.6%
0.05	29	0.4%
0.04	28	0.4%
0.03	28	0.4%
0.3	26	0.4%
0.49	25	0.4%
0.07	24	0.4%
0.06	21	0.3%
Other values (1436)	3405	50.5%
(Missing)	2960	43.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	104	1.5%
0.01	55	0.8%
0.02	40	0.6%
0.03	28	0.4%
0.04	28	0.4%

Value	Count	Frequency (%)
88.06	1	< 0.1%
87.95	1	< 0.1%
87.89	2	< 0.1%
85.99	1	< 0.1%
85.87	2	< 0.1%

people_fully_vaccinated_per_hundred
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING

Distinct	684
Distinct (%)	26.6%
Missing	4169
Missing (%)	61.8%
Infinite	0
Infinite (%)	0.0%

Mean	3.183276398
Minimum	0
Maximum	55.29
Zeros	47
Zeros (%)	0.7%
Memory size	52.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0.02
Q1	0.36
median	1.29
Q3	2.8225
95-th percentile	11.9225
Maximum	55.29
Range	55.29
Interquartile range (IQR)	2.4625

Descriptive statistics

Standard deviation	6.950445511
Coefficient of variation (CV)	2.183425076
Kurtosis	22.37056555
Mean	3.183276398
Median Absolute Deviation (MAD)	1.1
Skewness	4.547805927
Sum	8200.12
Variance	48.3086928
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.02	47	0.7%
0	47	0.7%
0.01	47	0.7%
0.04	40	0.6%
0.05	37	0.5%
0.07	37	0.5%
0.08	28	0.4%
0.29	27	0.4%
0.37	24	0.4%
0.1	21	0.3%
Other values (674)	2221	32.9%
(Missing)	4169	61.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	47	0.7%
0.01	47	0.7%
0.02	47	0.7%
0.03	20	0.3%
0.04	40	0.6%

Value	Count	Frequency (%)
55.29	1	< 0.1%
52.18	1	< 0.1%
50.4	1	< 0.1%
49.58	1	< 0.1%
49.05	2	< 0.1%

daily_vaccinations_per_million
Real number (ℝ_≥0)

MISSING

Distinct	3238
Distinct (%)	49.4%
Missing	195
Missing (%)	2.9%
Infinite	0
Infinite (%)	0.0%

Mean	2652.161832
Minimum	0
Maximum	54264
Zeros	5
Zeros (%)	0.1%
Memory size	52.8 KiB

Quantile statistics

Minimum	0
5-th percentile	34
Q1	363
median	1259.5
Q3	2961
95-th percentile	9599.6
Maximum	54264
Range	54264
Interquartile range (IQR)	2598

Descriptive statistics

Standard deviation	4250.226795
Coefficient of variation (CV)	1.602551829
Kurtosis	36.73066343
Mean	2652.161832
Median Absolute Deviation (MAD)	1023.5
Skewness	4.680763122
Sum	17371660
Variance	18064427.81
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
43	58	0.9%
4532	47	0.7%
469	40	0.6%
4184	40	0.6%
7492	39	0.6%
1356	34	0.5%
262	32	0.5%
178	29	0.4%
185	29	0.4%
5734	29	0.4%
Other values (3228)	6173	91.5%
(Missing)	195	2.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	5	0.1%
1	16	0.2%
2	13	0.2%
3	6	0.1%
4	5	0.1%

Value	Count	Frequency (%)
54264	8	0.1%
47947	1	< 0.1%
41344	1	< 0.1%
35027	1	< 0.1%
31700	1	< 0.1%

vaccines
Categorical

Distinct	26
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	52.8 KiB

Moderna, Oxford/AstraZeneca, Pfizer/BioNTech	1734
Pfizer/BioNTech	1276
Oxford/AstraZeneca, Pfizer/BioNTech	923
Oxford/AstraZeneca	602
Moderna, Pfizer/BioNTech	305
Other values (21)	1905

Length

Max length	82
Median length	35
Mean length	30.79866568
Min length	7

Characters and Unicode

Total characters	207737
Distinct characters	39
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Pfizer/BioNTech
2nd row	Pfizer/BioNTech
3rd row	Pfizer/BioNTech
4th row	Pfizer/BioNTech
5th row	Pfizer/BioNTech

Value	Count	Frequency (%)
Moderna, Oxford/AstraZeneca, Pfizer/BioNTech	1734	25.7%
Pfizer/BioNTech	1276	18.9%
Oxford/AstraZeneca, Pfizer/BioNTech	923	13.7%
Oxford/AstraZeneca	602	8.9%
Moderna, Pfizer/BioNTech	305	4.5%
Sputnik V	236	3.5%
Sinovac	200	3.0%
Pfizer/BioNTech, Sinovac	162	2.4%
Oxford/AstraZeneca, Pfizer/BioNTech, Sinopharm/Beijing, Sputnik V	151	2.2%
Sinopharm/Beijing	126	1.9%
Other values (16)	1030	15.3%

Histogram of lengths of the category

Value	Count	Frequency (%)
pfizer/biontech	4934	33.5%
oxford/astrazeneca	4003	27.2%
moderna	2241	15.2%
sinopharm/beijing	847	5.8%
v	833	5.7%
sputnik	833	5.7%
sinovac	526	3.6%
sinopharm/wuhan	161	1.1%
johnson&johnson	116	0.8%
epivaccorona	90	0.6%
Other values (3)	129	0.9%

Most occurring characters

Value	Count	Frequency (%)
e	21030	10.1%
r	16313	7.9%
i	14148	6.8%
o	13451	6.5%
a	12183	5.9%
n	10234	4.9%
/	9979	4.8%
c	9587	4.6%
f	8971	4.3%
	7968	3.8%
Other values (29)	83873	40.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	143680	69.2%
Uppercase Letter	38893	18.7%
Other Punctuation	17196	8.3%
Space Separator	7968	3.8%

Most frequent character per category

Value	Count	Frequency (%)
e	21030	14.6%
r	16313	11.4%
i	14148	9.8%
o	13451	9.4%
a	12183	8.5%
n	10234	7.1%
c	9587	6.7%
f	8971	6.2%
h	6369	4.4%
d	6244	4.3%
Other values (11)	25150	17.5%

Value	Count	Frequency (%)
B	5815	15.0%
P	4968	12.8%
N	4968	12.8%
T	4968	12.8%
O	4003	10.3%
A	4003	10.3%
Z	4003	10.3%
S	2367	6.1%
M	2241	5.8%
V	923	2.4%
Other values (4)	634	1.6%

Value	Count	Frequency (%)
/	9979	58.0%
,	7101	41.3%
&	116	0.7%

Value	Count	Frequency (%)
	7968	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	182573	87.9%
Common	25164	12.1%

Most frequent character per script

Value	Count	Frequency (%)
e	21030	11.5%
r	16313	8.9%
i	14148	7.7%
o	13451	7.4%
a	12183	6.7%
n	10234	5.6%
c	9587	5.3%
f	8971	4.9%
h	6369	3.5%
d	6244	3.4%
Other values (25)	64043	35.1%

Value	Count	Frequency (%)
/	9979	39.7%
	7968	31.7%
,	7101	28.2%
&	116	0.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	207737	100.0%

Most frequent character per block

Value	Count	Frequency (%)
e	21030	10.1%
r	16313	7.9%
i	14148	6.8%
o	13451	6.5%
a	12183	5.9%
n	10234	4.9%
/	9979	4.8%
c	9587	4.6%
f	8971	4.3%
	7968	3.8%
Other values (29)	83873	40.4%

source_name
Categorical

HIGH CARDINALITY

Distinct	81
Distinct (%)	1.2%
Missing	0
Missing (%)	0.0%
Memory size	52.8 KiB

Ministry of Health	2139
Government of the United Kingdom	465
Official data from provinces via covid19tracker.ca	93
Official data from local governments via gogov.ru	90
Federal Office of Public Health	90
Other values (76)	3868

Length

Max length	62
Median length	21
Mean length	26.3795404
Min length	9

Characters and Unicode

Total characters	177930
Distinct characters	53
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	Ministry of Health
2nd row	Ministry of Health
3rd row	Ministry of Health
4th row	Ministry of Health
5th row	Ministry of Health

Value	Count	Frequency (%)
Ministry of Health	2139	31.7%
Government of the United Kingdom	465	6.9%
Official data from provinces via covid19tracker.ca	93	1.4%
Official data from local governments via gogov.ru	90	1.3%
Federal Office of Public Health	90	1.3%
National Health Commission	90	1.3%
Government of Israel	88	1.3%
Centers for Disease Control and Prevention	87	1.3%
National Strategic Group on COVID-19	85	1.3%
Department of Statistics and Health Information	83	1.2%
Other values (71)	3435	50.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
of	4911	18.9%
health	3519	13.5%
ministry	2235	8.6%
government	2015	7.7%
the	723	2.8%
national	645	2.5%
public	567	2.2%
united	465	1.8%
kingdom	465	1.8%
for	462	1.8%
Other values (127)	10033	38.5%

Most occurring characters

Value	Count	Frequency (%)
	19295	10.8%
e	15747	8.9%
t	14577	8.2%
n	13579	7.6%
o	12953	7.3%
i	12155	6.8%
a	11703	6.6%
r	9920	5.6%
l	6734	3.8%
f	6415	3.6%
Other values (43)	54852	30.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	138331	77.7%
Space Separator	19295	10.8%
Uppercase Letter	18815	10.6%
Decimal Number	806	0.5%
Other Punctuation	373	0.2%
Dash Punctuation	310	0.2%

Most frequent character per category

Value	Count	Frequency (%)
e	15747	11.4%
t	14577	10.5%
n	13579	9.8%
o	12953	9.4%
i	12155	8.8%
a	11703	8.5%
r	9920	7.2%
l	6734	4.9%
f	6415	4.6%
s	5373	3.9%
Other values (15)	29175	21.1%

Value	Count	Frequency (%)
H	3729	19.8%
M	2572	13.7%
G	2484	13.2%
S	1340	7.1%
I	1202	6.4%
C	1137	6.0%
P	880	4.7%
D	796	4.2%
N	750	4.0%
K	633	3.4%
Other values (12)	3292	17.5%

Value	Count	Frequency (%)
.	266	71.3%
,	107	28.7%

Value	Count	Frequency (%)
1	403	50.0%
9	403	50.0%

Value	Count	Frequency (%)
	19295	100.0%

Value	Count	Frequency (%)
-	310	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	157146	88.3%
Common	20784	11.7%

Most frequent character per script

Value	Count	Frequency (%)
e	15747	10.0%
t	14577	9.3%
n	13579	8.6%
o	12953	8.2%
i	12155	7.7%
a	11703	7.4%
r	9920	6.3%
l	6734	4.3%
f	6415	4.1%
s	5373	3.4%
Other values (37)	47990	30.5%

Value	Count	Frequency (%)
	19295	92.8%
1	403	1.9%
9	403	1.9%
-	310	1.5%
.	266	1.3%
,	107	0.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	177930	100.0%

Most frequent character per block

Value	Count	Frequency (%)
	19295	10.8%
e	15747	8.9%
t	14577	8.2%
n	13579	7.6%
o	12953	7.3%
i	12155	6.8%
a	11703	6.6%
r	9920	5.6%
l	6734	3.8%
f	6415	3.6%
Other values (43)	54852	30.8%

source_website
Categorical

HIGH CARDINALITY

Distinct	133
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	52.8 KiB

https://coronavirus.data.gov.uk/details/healthcare	465
https://covid19tracker.ca/vaccinationtracker.html	93
https://gogov.ru/articles/covid-v-stats	90
https://www.chinadaily.com.cn/a/202103/15/WS604efbd6a31024ad0baaf3de.html	90
https://datadashboard.health.gov.il/COVID-19/general	88
Other values (128)	5919

Length

Max length	230
Median length	59
Mean length	68.85366938
Min length	16

Characters and Unicode

Total characters	464418
Distinct characters	73
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	https://shendetesia.gov.al/covid19-ministria-e-shendetesise-942-te-vaksinuar-3340-testime-872-te-sheruar-681-raste-te-reja-dhe-16-humbje-jete-ne-24-oret-e-fundit/
2nd row	https://shendetesia.gov.al/covid19-ministria-e-shendetesise-942-te-vaksinuar-3340-testime-872-te-sheruar-681-raste-te-reja-dhe-16-humbje-jete-ne-24-oret-e-fundit/
3rd row	https://shendetesia.gov.al/covid19-ministria-e-shendetesise-942-te-vaksinuar-3340-testime-872-te-sheruar-681-raste-te-reja-dhe-16-humbje-jete-ne-24-oret-e-fundit/
4th row	https://shendetesia.gov.al/covid19-ministria-e-shendetesise-942-te-vaksinuar-3340-testime-872-te-sheruar-681-raste-te-reja-dhe-16-humbje-jete-ne-24-oret-e-fundit/
5th row	https://shendetesia.gov.al/covid19-ministria-e-shendetesise-942-te-vaksinuar-3340-testime-872-te-sheruar-681-raste-te-reja-dhe-16-humbje-jete-ne-24-oret-e-fundit/

Value	Count	Frequency (%)
https://coronavirus.data.gov.uk/details/healthcare	465	6.9%
https://covid19tracker.ca/vaccinationtracker.html	93	1.4%
https://gogov.ru/articles/covid-v-stats	90	1.3%
https://www.chinadaily.com.cn/a/202103/15/WS604efbd6a31024ad0baaf3de.html	90	1.3%
https://datadashboard.health.gov.il/COVID-19/general	88	1.3%
https://covid.cdc.gov/covid-data-tracker/#vaccinations	87	1.3%
https://twitter.com/QNAEnglish/status/1371853178195607558	85	1.3%
https://healthalert.gov.bh/en/	84	1.2%
https://www.gob.mx/salud/prensa/111-vacunadas-personas-adultas-mayores-de-775-municipios-o-alcaldias?idiom=es	83	1.2%
https://www.gob.cl/yomevacuno/	83	1.2%
Other values (123)	5497	81.5%

Histogram of lengths of the category

Value	Count	Frequency (%)
https://coronavirus.data.gov.uk/details/healthcare	465	6.9%
https://covid19tracker.ca/vaccinationtracker.html	93	1.4%
https://www.chinadaily.com.cn/a/202103/15/ws604efbd6a31024ad0baaf3de.html	90	1.3%
https://gogov.ru/articles/covid-v-stats	90	1.3%
https://datadashboard.health.gov.il/covid-19/general	88	1.3%
https://covid.cdc.gov/covid-data-tracker/#vaccinations	87	1.3%
https://twitter.com/qnaenglish/status/1371853178195607558	85	1.3%
https://healthalert.gov.bh/en	84	1.2%
https://www.gob.cl/yomevacuno	83	1.2%
https://www.gob.mx/salud/prensa/111-vacunadas-personas-adultas-mayores-de-775-municipios-o-alcaldias?idiom=es	83	1.2%
Other values (123)	5497	81.5%

Most occurring characters

Value	Count	Frequency (%)
t	35189	7.6%
/	32725	7.0%
a	31154	6.7%
s	27330	5.9%
o	24763	5.3%
i	23816	5.1%
e	22453	4.8%
-	18933	4.1%
c	18580	4.0%
n	15484	3.3%
Other values (63)	213991	46.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	327553	70.5%
Other Punctuation	58358	12.6%
Decimal Number	48510	10.4%
Dash Punctuation	18933	4.1%
Uppercase Letter	9996	2.2%
Connector Punctuation	644	0.1%
Math Symbol	424	0.1%

Most frequent character per category

Value	Count	Frequency (%)
t	35189	10.7%
a	31154	9.5%
s	27330	8.3%
o	24763	7.6%
i	23816	7.3%
e	22453	6.9%
c	18580	5.7%
n	15484	4.7%
r	15060	4.6%
d	13665	4.2%
Other values (17)	100059	30.5%

Value	Count	Frequency (%)
D	1360	13.6%
C	1149	11.5%
V	866	8.7%
M	725	7.3%
A	723	7.2%
I	607	6.1%
O	588	5.9%
B	534	5.3%
S	497	5.0%
H	474	4.7%
Other values (15)	2473	24.7%

Value	Count	Frequency (%)
1	9853	20.3%
9	6629	13.7%
3	5422	11.2%
0	4529	9.3%
8	4124	8.5%
2	4048	8.3%
5	3599	7.4%
6	3572	7.4%
4	3432	7.1%
7	3302	6.8%

Value	Count	Frequency (%)
/	32725	56.1%
.	14963	25.6%
:	6745	11.6%
%	3327	5.7%
?	348	0.6%
#	167	0.3%
&	76	0.1%
,	7	< 0.1%

Value	Count	Frequency (%)
-	18933	100.0%

Value	Count	Frequency (%)
_	644	100.0%

Value	Count	Frequency (%)
=	424	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	337549	72.7%
Common	126869	27.3%

Most frequent character per script

Value	Count	Frequency (%)
t	35189	10.4%
a	31154	9.2%
s	27330	8.1%
o	24763	7.3%
i	23816	7.1%
e	22453	6.7%
c	18580	5.5%
n	15484	4.6%
r	15060	4.5%
d	13665	4.0%
Other values (42)	110055	32.6%

Value	Count	Frequency (%)
/	32725	25.8%
-	18933	14.9%
.	14963	11.8%
1	9853	7.8%
:	6745	5.3%
9	6629	5.2%
3	5422	4.3%
0	4529	3.6%
8	4124	3.3%
2	4048	3.2%
Other values (11)	18898	14.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	464392	> 99.9%
None	26	< 0.1%

Most frequent character per block

Value	Count	Frequency (%)
t	35189	7.6%
/	32725	7.0%
a	31154	6.7%
s	27330	5.9%
o	24763	5.3%
i	23816	5.1%
e	22453	4.8%
-	18933	4.1%
c	18580	4.0%
n	15484	3.3%
Other values (62)	213965	46.1%

Value	Count	Frequency (%)
ñ	26	100.0%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	country	iso_code	date	total_vaccinations	people_vaccinated	people_fully_vaccinated	daily_vaccinations_raw	daily_vaccinations	total_vaccinations_per_hundred	people_vaccinated_per_hundred	people_fully_vaccinated_per_hundred	daily_vaccinations_per_million	vaccines	source_name	source_website
0	Albania	ALB	2021-01-10	0.0	0.0	NaN	NaN	NaN	0.00	0.00	NaN	NaN	Pfizer/BioNTech	Ministry of Health	https://shendetesia.gov.al/covid19-ministria-e-shendetesise-942-te-vaksinuar-3340-testime-872-te-sheruar-681-raste-te-reja-dhe-16-humbje-jete-ne-24-oret-e-fundit/
1	Albania	ALB	2021-01-11	NaN	NaN	NaN	NaN	64.0	NaN	NaN	NaN	22.0	Pfizer/BioNTech	Ministry of Health	https://shendetesia.gov.al/covid19-ministria-e-shendetesise-942-te-vaksinuar-3340-testime-872-te-sheruar-681-raste-te-reja-dhe-16-humbje-jete-ne-24-oret-e-fundit/
2	Albania	ALB	2021-01-12	128.0	128.0	NaN	NaN	64.0	0.00	0.00	NaN	22.0	Pfizer/BioNTech	Ministry of Health	https://shendetesia.gov.al/covid19-ministria-e-shendetesise-942-te-vaksinuar-3340-testime-872-te-sheruar-681-raste-te-reja-dhe-16-humbje-jete-ne-24-oret-e-fundit/
3	Albania	ALB	2021-01-13	188.0	188.0	NaN	60.0	63.0	0.01	0.01	NaN	22.0	Pfizer/BioNTech	Ministry of Health	https://shendetesia.gov.al/covid19-ministria-e-shendetesise-942-te-vaksinuar-3340-testime-872-te-sheruar-681-raste-te-reja-dhe-16-humbje-jete-ne-24-oret-e-fundit/
4	Albania	ALB	2021-01-14	266.0	266.0	NaN	78.0	66.0	0.01	0.01	NaN	23.0	Pfizer/BioNTech	Ministry of Health	https://shendetesia.gov.al/covid19-ministria-e-shendetesise-942-te-vaksinuar-3340-testime-872-te-sheruar-681-raste-te-reja-dhe-16-humbje-jete-ne-24-oret-e-fundit/
5	Albania	ALB	2021-01-15	308.0	308.0	NaN	42.0	62.0	0.01	0.01	NaN	22.0	Pfizer/BioNTech	Ministry of Health	https://shendetesia.gov.al/covid19-ministria-e-shendetesise-942-te-vaksinuar-3340-testime-872-te-sheruar-681-raste-te-reja-dhe-16-humbje-jete-ne-24-oret-e-fundit/
6	Albania	ALB	2021-01-16	369.0	369.0	NaN	61.0	62.0	0.01	0.01	NaN	22.0	Pfizer/BioNTech	Ministry of Health	https://shendetesia.gov.al/covid19-ministria-e-shendetesise-942-te-vaksinuar-3340-testime-872-te-sheruar-681-raste-te-reja-dhe-16-humbje-jete-ne-24-oret-e-fundit/
7	Albania	ALB	2021-01-17	405.0	405.0	NaN	36.0	58.0	0.01	0.01	NaN	20.0	Pfizer/BioNTech	Ministry of Health	https://shendetesia.gov.al/covid19-ministria-e-shendetesise-942-te-vaksinuar-3340-testime-872-te-sheruar-681-raste-te-reja-dhe-16-humbje-jete-ne-24-oret-e-fundit/
8	Albania	ALB	2021-01-18	447.0	447.0	NaN	42.0	55.0	0.02	0.02	NaN	19.0	Pfizer/BioNTech	Ministry of Health	https://shendetesia.gov.al/covid19-ministria-e-shendetesise-942-te-vaksinuar-3340-testime-872-te-sheruar-681-raste-te-reja-dhe-16-humbje-jete-ne-24-oret-e-fundit/
9	Albania	ALB	2021-01-19	483.0	483.0	NaN	36.0	51.0	0.02	0.02	NaN	18.0	Pfizer/BioNTech	Ministry of Health	https://shendetesia.gov.al/covid19-ministria-e-shendetesise-942-te-vaksinuar-3340-testime-872-te-sheruar-681-raste-te-reja-dhe-16-humbje-jete-ne-24-oret-e-fundit/

Last rows

	country	iso_code	date	total_vaccinations	people_vaccinated	people_fully_vaccinated	daily_vaccinations_raw	daily_vaccinations	total_vaccinations_per_hundred	people_vaccinated_per_hundred	people_fully_vaccinated_per_hundred	daily_vaccinations_per_million	vaccines	source_name	source_website
6735	Zimbabwe	ZWE	2021-03-07	32240.0	32240.0	NaN	226.0	1914.0	0.22	0.22	NaN	129.0	Sinopharm/Beijing	Ministry of Health	https://twitter.com/MoHCCZim/status/1371917996193689606
6736	Zimbabwe	ZWE	2021-03-08	35518.0	35518.0	NaN	3278.0	2009.0	0.24	0.24	NaN	135.0	Sinopharm/Beijing	Ministry of Health	https://twitter.com/MoHCCZim/status/1371917996193689606
6737	Zimbabwe	ZWE	2021-03-09	35761.0	35761.0	NaN	243.0	1526.0	0.24	0.24	NaN	103.0	Sinopharm/Beijing	Ministry of Health	https://twitter.com/MoHCCZim/status/1371917996193689606
6738	Zimbabwe	ZWE	2021-03-10	35901.0	35901.0	NaN	140.0	1133.0	0.24	0.24	NaN	76.0	Sinopharm/Beijing	Ministry of Health	https://twitter.com/MoHCCZim/status/1371917996193689606
6739	Zimbabwe	ZWE	2021-03-11	36019.0	36019.0	NaN	118.0	766.0	0.24	0.24	NaN	52.0	Sinopharm/Beijing	Ministry of Health	https://twitter.com/MoHCCZim/status/1371917996193689606
6740	Zimbabwe	ZWE	2021-03-12	36283.0	36283.0	NaN	264.0	708.0	0.24	0.24	NaN	48.0	Sinopharm/Beijing	Ministry of Health	https://twitter.com/MoHCCZim/status/1371917996193689606
6741	Zimbabwe	ZWE	2021-03-13	36359.0	36359.0	NaN	76.0	621.0	0.24	0.24	NaN	42.0	Sinopharm/Beijing	Ministry of Health	https://twitter.com/MoHCCZim/status/1371917996193689606
6742	Zimbabwe	ZWE	2021-03-14	36359.0	36359.0	NaN	0.0	588.0	0.24	0.24	NaN	40.0	Sinopharm/Beijing	Ministry of Health	https://twitter.com/MoHCCZim/status/1371917996193689606
6743	Zimbabwe	ZWE	2021-03-15	37660.0	37660.0	NaN	1301.0	306.0	0.25	0.25	NaN	21.0	Sinopharm/Beijing	Ministry of Health	https://twitter.com/MoHCCZim/status/1371917996193689606
6744	Zimbabwe	ZWE	2021-03-16	39550.0	39550.0	NaN	1890.0	541.0	0.27	0.27	NaN	36.0	Sinopharm/Beijing	Ministry of Health	https://twitter.com/MoHCCZim/status/1371917996193689606

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows